Flood Risk Pattern Recognition Using Integrated Chemometric Method and Artificial Neural Network: A Case Study in the Johor River Basin

Azid, Azman and Juahir, Hafizan and Toriman, Mohd Ekhwan and Kamarudin, Mohd Khairul Amri (2015) Flood Risk Pattern Recognition Using Integrated Chemometric Method and Artificial Neural Network: A Case Study in the Johor River Basin. Jurnal Teknologi, 74 (1). pp. 165-170. ISSN 0127–9696

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Abstract

Flood is a major problem in Johor river basin, which normally happened during monsoon season. However in this study, it shows that rainfall did not have a strong relationship for the changes of water level compared to suspended solid and stream flow, where both variables have p-values of <0.0001 and these variables also became the main factors in contributing to the flood occurrence based on Factor Analysis result. Time Series Analysis was being carried out and based on Statistical Process Control, the limitation has been set up for mitigation in controlling flood. All data beyond the Upper Control Limit was predicted to have High Risk to face flood and Emergency Response Plan should be implemented to prevent complication and destruction because of flood. The prediction for the risk level was carried out using the application of Artificial Neural Network (ANN), where the accuracy of prediction was very high, with the result of 96% for the level of accuracy in the prediction of risk class.

Item Type: Article
Keywords: Flood; monsoon; factor analysis; time series analysis; statistical process control; artificial neural network
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
H Social Sciences > HA Statistics
Q Science > Q Science (General)
Q Science > QA Mathematics
Faculty / Institute: East Coast Environmental Research Institute (ESERI)
Depositing User: Dr Azman Azid
Date Deposited: 22 Jun 2015 00:50
Last Modified: 25 Oct 2015 00:00
URI: http://erep.unisza.edu.my/id/eprint/3405

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